Mixed reality participants in smart meeting rooms and smart home enviroments

Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments

Towards Simulating Humans in Augmented Multi-party Interaction

Human-computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in the European AMI research project

No Grice: Computers that Lie, Deceive and Conceal

In the future our daily life interactions with other people, with computers, robots and smart environments will be recorded and interpreted by computers or embedded intelligence in environments, furniture, robots, displays, and wearables. These sensors record our activities, our behavior, and our interactions. Fusion of such information and reasoning about such information makes it possible, using computational models of human behavior and activities, to provide context- and person-aware interpretations of human behavior and activities, including determination of attitudes, moods, and emotions. Sensors include cameras, microphones, eye trackers, position and proximity sensors, tactile or smell sensors, et cetera. Sensors can be embedded in an environment, but they can also move around, for example, if they are part of a mobile social robot or if they are part of devices we carry around or are embedded in our clothes or body. \ud \ud Our daily life behavior and daily life interactions are recorded and interpreted. How can we use such environments and how can such environments use us? Do we always want to cooperate with these environments; do these environments always want to cooperate with us? In this paper we argue that there are many reasons that users or rather human partners of these environments do want to keep information about their intentions and their emotions hidden from these smart environments. On the other hand, their artificial interaction partner may have similar reasons to not give away all information they have or to treat their human partner as an opponent rather than someone that has to be supported by smart technology.\ud \ud This will be elaborated in this paper. We will survey examples of human-computer interactions where there is not necessarily a goal to be explicit about intentions and feelings. In subsequent sections we will look at (1) the computer as a conversational partner, (2) the computer as a butler or diary companion, (3) the computer as a teacher or a trainer, acting in a virtual training environment (a serious game), (4) sports applications (that are not necessarily different from serious game or education environments), and games and entertainment applications

Emerging research directions in computer science : contributions from the young informatics faculty in Karlsruhe

In order to build better human-friendly human-computer interfaces, such interfaces need to be enabled with capabilities to perceive the user, his location, identity, activities and in particular his interaction with others and the machine. Only with these perception capabilities can smart systems ( for example human-friendly robots or smart environments) become posssible. In my research I\u27m thus focusing on the development of novel techniques for the visual perception of humans and their activities, in order to facilitate perceptive multimodal interfaces, humanoid robots and smart environments. My work includes research on person tracking, person identication, recognition of pointing gestures, estimation of head orientation and focus of attention, as well as audio-visual scene and activity analysis. Application areas are humanfriendly humanoid robots, smart environments, content-based image and video analysis, as well as safety- and security-related applications. This article gives a brief overview of my ongoing research activities in these areas

From Word Play to World Play: Introducing Humor in Human-Computer Interaction

Humor is important in our life, whether it is at home, at work, or in public spaces. Smart technology is increasingly becoming part of our daily life. Can smart technology, sensors and actuators, not only be used to introduce smartness in our environments, but also to introduce amusement? So far understanding of humor has escaped algorithmic approaches. Nevertheless, humor research knowledge is available and is increasing. First philosophers, then psychologists, then linguists and AI researchers made humor topic of their research. The aim of this paper is to introduce humor research to the human-computer interaction community. In particular we look at how our digitally enhanced physical worlds, or smart environments, can facilitate humor creation

Introducing Neuroberry, a platform for pervasive EEG signaling in the IoT domain

The emergence of inexpensive off-the-shelf wireless EEG devices led researchers to explore novel paradigms in the field of Human Computer Interaction. In fact, the compliance of these devices with the IoT principles towards pervasive EEG signaling in smart home environments enables new models of interaction and a different perspective from traditional affective computing. In this paper, the implementation of wireless EEG (Emotiv EPOC and Mindawave) IoT connectivity of real time raw signals, through IoT hardware devices and through the Raspberry Pi 2, is presented

An XRI Mixed-Reality Internet-of-Things Architectural Framework Toward Immersive and Adaptive Smart Environments

The internet-of-things (IoT) refers to the growing number of embedded interconnected devices within everyday ubiquitous objects and environments, especially their networks, edge controllers, data gathering and management, sharing, and contextual analysis capabilities. However, the IoT suffers from inherent limitations in terms of human-computer interaction. In this landscape, there is a need for interfaces that have the potential to translate the IoT more solidly into the foreground of everyday smart environments, where its users are multimodal, multifaceted, and where new forms of presentation, adaptation, and immersion are essential. This work highlights the synergetic opportunities for both IoT and XR to converge toward hybrid XR objects with strong real-world connectivity, and IoT objects with rich XR interfaces. The paper contributes i) an understanding of this multi-disciplinary domain XR-IoT (XRI); ii) a theoretical perspective on how to design XRI agents based on the literature; iii) a system design architectural framework for XRI smart environment development; and iv) an early discussion of this process. It is hoped that this research enables future researchers in both communities to better understand and deploy hybrid smart XRI environments

Customizing smart environments: a tabletop approach

Smart environments are becoming a reality in our society and the number of intelligent devices integrated in these spaces is in-creasing very rapidly. As the combination of intelligent elements will open a wide range of new opportunities to make our lives easier, final users should be provided with a simplified method of handling complex intelligent features. Specifying behavior in these environments can be difficult for non-experts, so that more efforts should be directed towards easing the customization tasks. This work presents an entirely visual rule editor based on dataflow expressions for interactive tabletops which allows be-havior to be specified in smart environments. An experiment was carried out aimed at evaluating the usability of the editor in terms of non-programmers understanding of the abstractions and concepts involved in the rule model, ease of use of the pro-posed visual interface and the suitability of the interaction mechanisms implemented in the editing tool. The study revealed that users with no previous programming experience were able to master the proposed rule model and editing tool for specifying be-havior in the context of a smart home, even though some minor usability issues were detected.We would like to thank all the volunteers that participated in the empirical study. Our thanks are also due to the ASIC/Polimedia team for their computer hardware support. This work was partially funded by the Spanish Ministry of Science and Innovation under the National R&D&I Program within the project CreateWorlds (TIN2010-20488). It also received support from a postdoctoral fellowship within the VALi+d Program of the Conselleria d'Educacio, Cultura I Esport (Generalitat Valenciana) awarded to Alejandro Catala (APOSTD/2013/013). 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Envisioning Future Playful Interactive Environments for Animals

The final publication is available at Springer via http://dx.doi.org/10.1007/978-981-287-546-4_6Play stands as one of the most natural and inherent behavior among the majority of living species, specifically humans and animals. Human play has evolved significantly over the years, and so have done the artifacts which allow us to play: from children playing tag games without any tools other than their bodies, to modern video games using haptic and wearable devices to augment the playful experience. However, this ludic revolution has not been the same for the humans’ closest companions, our pets. Recently, a new discipline inside the human–computer interaction (HCI) community, called animal–computer interaction (ACI), has focused its attention on improving animals’ welfare using technology. Several works in the ACI field rely on playful interfaces to mediate this digital communication between animals and humans. Until now, the development of these interfaces only comprises a single goal or activity, and its adaptation to the animals’ needs requires the developers’ intervention. This work analyzes the existing approaches, proposing a more generic and autonomous system aimed at addressing several aspects of animal welfare at a time: Intelligent Playful Environments for Animals. The great potential of these systems is discussed, explaining how incorporating intelligent capabilities within playful environments could allow learning from the animals’ behavior and automatically adapt the game to the animals’ needs and preferences. The engaging playful activities created with these systems could serve different purposes and eventually improve animals’ quality of life.This work was partially funded by the Spanish Ministry of Science andInnovation under the National R&D&I Program within the projects Create Worlds (TIN2010-20488) and SUPEREMOS (TIN2014-60077-R), and from Universitat Politècnica de València under Project UPV-FE-2014-24. It also received support from a postdoctoral fellowship within theVALi+d Program of the Conselleria d’Educació, Cultura I Esport (Generalitat Valenciana) awarded to Alejandro Catalá (APOSTD/2013/013). The work of Patricia Pons has been supported by the Universitat Politècnica de València under the “Beca de Excelencia” program and currently by an FPU fellowship from the Spanish Ministry of Education, Culture, and Sports (FPU13/03831).Pons Tomás, P.; Jaén Martínez, FJ.; Catalá Bolós, A. (2015). Envisioning Future Playful Interactive Environments for Animals. 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Channel State Information from pure communication to sense and track human motion: A survey

Human motion detection and activity recognition are becoming vital for the applications in smart homes. Traditional Human Activity Recognition (HAR) mechanisms use special devices to track human motions, such as cameras (vision-based) and various types of sensors (sensor-based). These mechanisms are applied in different applications, such as home security, Human–Computer Interaction (HCI), gaming, and healthcare. However, traditional HAR methods require heavy installation, and can only work under strict conditions. Recently, wireless signals have been utilized to track human motion and HAR in indoor environments. The motion of an object in the test environment causes fluctuations and changes in the Wi-Fi signal reflections at the receiver, which result in variations in received signals. These fluctuations can be used to track object (i.e., a human) motion in indoor environments. This phenomenon can be improved and leveraged in the future to improve the internet of things (IoT) and smart home devices. The main Wi-Fi sensing methods can be broadly categorized as Received Signal Strength Indicator (RSSI), Wi-Fi radar (by using Software Defined Radio (SDR)) and Channel State Information (CSI). CSI and RSSI can be considered as device-free mechanisms because they do not require cumbersome installation, whereas the Wi-Fi radar mechanism requires special devices (i.e., Universal Software Radio Peripheral (USRP)). Recent studies demonstrate that CSI outperforms RSSI in sensing accuracy due to its stability and rich information. This paper presents a comprehensive survey of recent advances in the CSI-based sensing mechanism and illustrates the drawbacks, discusses challenges, and presents some suggestions for the future of device-free sensing technology